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Distinct Molecular Signatures of Clinical Clusters in People With Type 2 Diabetes: An IMI-RHAPSODY Study

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Roderick C. Slieker, Louise A. Donnelly, Hugo Fitipaldi, Gerard A. Bouland, Giuseppe N. Giordano, Mikael Åkerlund, Mathias J. Gerl, Emma Ahlqvist, Ashfaq Ali, Iulian Dragan, Petra Elders, Andreas Festa, Michael K. Hansen, Amber A. van der Heijden, Dina Mansour Aly, Min Kim, Dmitry Kuznetsov, Florence Mehl, Christian Klose, Kai Simons & 15 more Imre Pavo, Timothy J. Pullen, Tommi Suvitaival, Asger Wretlind, Peter Rossing, Valeriya Lyssenko, Cristina Legido Quigley, Leif Groop, Bernard Thorens, Paul W. Franks, Mark Ibberson, Guy A. Rutter, Joline W.J. Beulens, Leen M. 't Hart, Ewan R. Pearson

Original languageEnglish
Pages (from-to)2683-2693
Number of pages11
Issue number11
Published1 Nov 2021

Bibliographical note

Publisher Copyright: © 2021 by the American Diabetes Association.

King's Authors


Type 2 diabetes is a multifactorial disease with multiple underlying aetiologies. To address this heterogeneity, investigators of a previous study clustered people with diabetes according to five diabetes subtypes. The aim of the current study is to investigate the etiology of these clusters by comparing their molecular signatures. In three independent cohorts, in total 15,940 individuals were clustered based on five clinical characteristics. In a subset, genetic (N = 12,828), metabolomic (N = 2,945), lipidomic (N = 2,593), and proteomic (N = 1,170) data were obtained in plasma. For each data type, each cluster was compared with the other four clusters as the reference. The insulin-resistant cluster showed the most distinct molecular signature, with higher branched-chain amino acid, diacylglycerol, and triacylglycerol levels and aberrant protein levels in plasma were enriched for proteins in the intracellular PI3K/Akt pathway. The obese cluster showed higher levels of cytokines. The mild diabetes cluster with high HDL showed the most beneficial molecular profile with effects opposite of those seen in the insulin-resistant cluster. This study shows that clustering people with type 2 diabetes can identify underlying molecular mechanisms related to pancreatic islets, liver, and adipose tissue metabolism. This provides novel biological insights into the diverse aetiological processes that would not be evident when type 2 diabetes is viewed as a homogeneous disease.

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